On Wed, 19 Jun 2019 at 07:42, King Jiefei wrote:
>
> Hello Kevin and Iñaki,
>
> Thanks for your quick responses. I sincerely appreciate them! I can see how
> complicated it is to interact with R in C. Iñaki's suggestion is very
> helpful, I saw there is a lot of performance gain by turning the
Hello Kevin and Iñaki,
Thanks for your quick responses. I sincerely appreciate them! I can see how
complicated it is to interact with R in C. Iñaki's suggestion is very
helpful, I saw there is a lot of performance gain by turning the flag on,
but sadly the best performance it can offer still
On Tue, 18 Jun 2019 at 19:41, King Jiefei wrote:
>
> [...]
>
> It is clear to see that calling an R function in R is the fast one, it is
> about 5X faster than ` R_forceAndCall ` and ` Rf_eval`. the latter two
> functions have a similar performance and using Rcpp is the worst one. Is it
>
For reference, your benchmark using UNWIND_PROTECT:
> system.time(test(testFunc, evn$x))
user system elapsed
0.331 0.000 0.331
> system.time(test(C_test1, testFunc, evn$x))
user system elapsed
2.029 0.000 2.036
> system.time(test(C_test2, expr, evn))
user system elapsed
Hi Jiefei,
Calling into R from C++ code is more complicated than one might think.
Please see Tomas Kalibera's post here:
https://developer.r-project.org/Blog/public/2019/03/28/use-of-c---in-packages/index.html
The Rcpp Function class is more expensive than a regular Rf_eval()
because it tries to
Hi,
I'm looking for a most efficient way to call an R function from C++ in a
package. I know there are two functions (`R_forceAndCall` and `Rf_eval`)
that can do the "call" part, but both are slow compared to calling the same
function in R. I also try to use Rcpp and it is the worse one. Here is
